Check computer science papers: citations, claims and retractions

When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale

Marion, M., Üstün, A., Pozzobon, L., Wang, A., Fadaee, M., & Hooker, S. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 11

Cloud-supported machine learning system for context-aware adaptive M-learning

ADNAN, M., HABIB, A., ASHRAF, J., & MUSSADIQ, S. (2019) · TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES

Intelligent Tutoring Systems and Adaptive LearningOnline Learning and Analytics

Cited by 11

VRCCS-AC: Reinforcement Learning for Service Migration in Vehicular Edge Computing Systems

Gao, Z., Yang, L., & Dai, Y. (2024) · IEEE Transactions on Services Computing

IoT and Edge/Fog ComputingVehicular Ad Hoc Networks (VANETs)

Cited by 11

STEVE-1: A Generative Model for Text-to-Behavior in Minecraft

Lifshitz, S., Paster, K., Chan, H., Ba, J., & McIlraith, S. (2023) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 11

Semantic Segmentation for Autonomous Driving: Model Evaluation, Dataset Generation, Perspective Comparison, and Real-Time Capability

Cakir, S., Gauß, M., Häppeler, K., Ounajjar, Y., Heinle, F., & Marchthaler, R. (2022) · arXiv

Advanced Neural Network ApplicationsAutonomous Vehicle Technology and Safety

Cited by 11

Enhancing generative AI reliability via agentic AI in 6G-enabled edge computing

Ale, L., King, S. A., Zhang, N., & Xing, H. (2025) · Nature Reviews Electrical Engineering

IoT and Edge/Fog ComputingArtificial Intelligence Applications

Cited by 11

Understanding Man-in-the-middle-attack through Survey of Literature

Mallik, A., Ahsan, A., Shahadat, M. M. Z., & Tsou, J. C. (2019) · Indonesian Journal of Computing, Engineering and Design (IJoCED)

Advanced Authentication Protocols SecurityInformation and Cyber Security

Cited by 11

Mobile Forensics for Cyberbullying Detection using Term Frequency - Inverse Document Frequency (TF-IDF)

Riadi, I., Sunardi, S., & Widiandana, P. (2020) · Jurnal Ilmiah Teknik Elektro Komputer dan Informatika

Hate Speech and Cyberbullying DetectionDigital and Cyber Forensics

Cited by 11

Can Anybody Help Me?: Using Community Help Desk Call Records to Examine the Impact of Digital Divides During a Global Pandemic

Biehl, J. T., Farzan, R., & Zhou, Y. (2022) · CHI Conference on Human Factors in Computing Systems

ICT in Developing CommunitiesICT Impact and Policies

Cited by 11

Aesthetic Post-Training Diffusion Models from Generic Preferences with Step-by-step Preference Optimization

Liang, Z., Yuan, Y., Gu, S., Chen, B., Hang, T., Cheng, M., Li, J., & Zheng, L. (2025) · 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Generative Adversarial Networks and Image SynthesisMultimodal Machine Learning Applications

Cited by 11

EducationQ: Evaluating LLMs' Teaching Capabilities Through Multi-Agent Dialogue Framework

Shi, Y., Liang, R., & Xu, Y. (2025) · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Intelligent Tutoring Systems and Adaptive LearningArtificial Intelligence in Education

Cited by 11

“Was it “stated” or was it “claimed”?: How linguistic bias affects generative language models

Patel, R., & Pavlick, E. (2021) · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Sentiment Analysis and Opinion MiningTopic Modeling

Cited by 11

Constructing Large-Scale Real-World Benchmark Datasets for AIOps

Li, Z., Zhao, N., Zhang, S., Sun, Y., Chen, P., Wen, X., Ma, M., & Pei, D. (2022) · arXiv

Software System Performance and ReliabilityCloud Computing and Resource Management

Cited by 11

Data Agency Theory: A Precise Theory of Justice for AI Applications

Ajmani, L., Stapleton, L., Houtti, M., & Chancellor, S. (2024) · The 2024 ACM Conference on Fairness Accountability and Transparency

Ethics and Social Impacts of AIDigitalization, Law, and Regulation

Cited by 11

Follow the Successful Herd: Towards Explanations for Improved Use and Mental Models of Natural Language Systems

Brachman, M., Pan, Q., Do, H. J., Dugan, C., Chaudhary, A., Johnson, J. M., Rai, P., Chakraborti, T., Gschwind, T., Laredo, J. A., et al. (2023) · Proceedings of the 28th International Conference on Intelligent User Interfaces

Explainable Artificial Intelligence (XAI)Usability and User Interface Design

Cited by 11

SLiC-HF: Sequence Likelihood Calibration with Human Feedback

Zhao, Y., Joshi, R., Liu, T., Khalman, M., Saleh, M., & Liu, P. J. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 11

HonestLLM: Toward an Honest and Helpful Large Language Model

Gao, C., Wu, S., Huang, Y., Chen, D., Zhang, Q., Fu, Z., Wan, Y., Sun, L., & Zhang, X. (2024) · arXiv

Ethics and Social Impacts of AITopic Modeling

Cited by 11

Edge Workloads Monitoring and Failover: A StarlingX-Based Testbed Implementation and Measurement Study

Abuibaid, M., Ghorab, A. H., Seguin-Mcpeake, A., Yuen, O., Yungblut, T., & St-Hilaire, M. (2022) · IEEE Access

IoT and Edge/Fog ComputingCloud Computing and Resource Management

Cited by 11

iVUN: interactive Visualization of Uncertain biochemical reaction Networks

Vehlow, C., Hasenauer, J., Kramer, A., Raue, A., Hug, S., Timmer, J., Radde, N., Theis, F. J., & Weiskopf, D. (2013) · BMC Bioinformatics

Data Visualization and AnalyticsGene Regulatory Network Analysis

Cited by 11

V2X-Boosted Federated Learning for Cooperative Intelligent Transportation Systems with Contextual Client Selection

Song, R., Lyu, L., Jiang, W., Festag, A., & Knoll, A. (2023) · arXiv

Privacy-Preserving Technologies in DataVehicular Ad Hoc Networks (VANETs)

Cited by 11

Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment

Ball, P. J., Lu, C., Parker-Holder, J., & Roberts, S. (2021) · arXiv

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 11

Workflow extraction for service operation using multiple unstructured trouble tickets

Watanabe, A., Ishibashi, K., Toyono, T., Kimura, T., Watanabe, K., Matsuo, Y., & Shiomoto, K. (2016) · NOMS 2016 - 2016 IEEE/IFIP Network Operations and Management Symposium

Software System Performance and ReliabilityBusiness Process Modeling and Analysis

Cited by 11

Understanding plasticity in neural networks

Lyle, C., Zheng, Z., Nikishin, E., Pires, B. A., Pascanu, R., & Dabney, W. (2023) · arXiv

Reinforcement Learning in RoboticsNeural Networks and Applications

Cited by 11

Federated machine learning for a facilitated implementation of Artificial Intelligence in healthcare – a proof of concept study for the prediction of coronary artery calcification scores

Wolff, J., Matschinske, J., Baumgart, D., Pytlik, A., Keck, A., Natarajan, A., von Schacky, C. E., Pauling, J. K., & Baumbach, J. (2022) · Journal of Integrative Bioinformatics

Privacy-Preserving Technologies in DataArtificial Intelligence in Healthcare and Education

Cited by 11